Java Data Engineer with AI

re-zoo-me; Virginia (MN); Hybrid; USD 120,000 - 160,000; Full time

Job summary

re-zoo-me seeks a Java Data Engineer with AI expertise to design, build, and maintain scalable data pipelines and curated datasets. You will work with Java, Spring Boot, Python, SQL, and AWS cloud-native services, including Spark, Kafka, and DynamoDB.

The role emphasizes data quality, observability, automation, and AI-assisted development practices within an Agile/Scrum environment. Onsite in McLean, VA or Chicago, IL.

Qualifications

• Experience with Java and Spring Boot.
• Strong Python and SQL skills.
• Experience with AWS data engineering services.
• Hands-on use of DynamoDB, EMR, EC2, Spark and Kafka.
• Ability to design scalable data pipelines and transformations.
• Experience with deployment, troubleshooting, and automated testing.
• Strong data quality, monitoring, and observability.

Responsibilities

• Design, develop, and maintain scalable data pipelines and datasets.
• Build data-intensive apps using Java, Spring Boot, Python, and SQL.
• Develop cloud-native data solutions using AWS services.
• Leverage DynamoDB, EMR, EC2, Spark, and Kafka for data processing.
• Create batch and real-time data pipelines for analytics and operations.
• Implement data integration, validation, and processing frameworks.
• Handle deployment, troubleshooting, and production support.
• Implement automated testing and ensure data quality and observability.
• Collaborate with developers, data engineers, and stakeholders.

Skills

Java

Spring Boot

Python

SQL

Agile/Scrum

Data pipelines

Data transformations

Cloud-native data

AI-assisted development

Data quality

Observability

Automated testing

Problem solving

Tools

DynamoDB

Amazon EMR

Amazon EC2

Apache Spark

Apache Kafka

Job description

Java Data Engineer with AI

Location: McLean, VA or Chicago, IL /Onsite

Visa : GC / USC / H4 EAD

Exp : 10 + Yrs

Job Summary

We are seeking an experienced Java Data Engineer with AI expertise to design, build, and maintain scalable data pipelines, data transformations, and curated datasets. The ideal candidate will have strong hands‑on experience with Java, Spring Boot, Python, SQL, AWS cloud-native data services, Spark, Kafka, and DynamoDB.

This role will work across modern cloud and big data platforms to deliver reliable, high-quality, and scalable data solutions supporting both analytical and operational use cases. Experience leveraging AI-assisted development tools and methodologies is highly desirable.

Key Responsibilities

• Design, develop, and maintain scalable data pipelines, transformations, and curated datasets.
• Build data-intensive applications and services using Java, Spring Boot, Python, and SQL.
• Develop cloud-native data solutions using AWS services and infrastructure.
• Work with DynamoDB, EMR, EC2, Spark, and Kafka to build and support high-volume data processing solutions.
• Develop batch and real-time data pipelines supporting analytical and operational workloads.
• Implement data integration, transformation, validation, and processing frameworks.
• Perform application and data pipeline deployment, troubleshooting, performance tuning, and production support.
• Implement automated testing and ensure data pipelines meet reliability and quality standards.
• Establish and maintain data quality, monitoring, observability, and operational controls.
• Collaborate with application developers, data engineers, architects, DevOps, and business stakeholders.
• Apply AI-assisted development practices to improve engineering productivity, code quality, testing, and solution delivery.
• Participate in Agile development activities, including design, development, code reviews, testing, deployment, and production support.

Required Skills

• Strong hands‑on experience with Java and Spring Boot.
• Proficiency in Python and SQL.
• Strong experience in AWS cloud-native data engineering.
• Hands‑on experience with:
• Amazon DynamoDB
• Amazon EMR
• Amazon EC2
• Apache Spark
• Apache Kafka
• Experience designing and implementing scalable data pipelines and data transformations.
• Experience with deployment, troubleshooting, and automated testing.
• Strong understanding of data quality, monitoring, and observability.
• Experience working in Agile/Scrum development environments.
• Strong analytical and problem‑solving skills.

AI / Modern Development Experience

• Experience using Claude or other AI-assisted development tools.
• Familiarity with Spec-Driven Development (Spec-Driven) approaches.
• Experience with BMAD (Breakthrough Method for Agile AI-Driven Development) or similar AI-assisted software development methodologies.
• Ability to leverage AI tools for requirements analysis, code generation, testing, documentation, and developer productivity.

Preferred Qualifications

• Prior experience with Capital one is a plus.
• Experience working with large-scale distributed data platforms.
• Experience with real-time/streaming data architectures.
• Experience with cloud-native application and data platform modernization.
• Financial services or banking domain experience is a plus.
• Strong communication and collaboration skills.

Core Technologies

Java | Spring Boot | Python | SQL | AWS | DynamoDB | EMR | EC2 | Spark | Kafka | Data Pipelines | Data Quality | Observability | Automated Testing | Claude | Spec-Driven Development | BMAD